> (setf nums nil)
NIL
> (dolist (x '(5 8 4 2 1 9 6 7 3))
    (setf nums (bst-insert x nums #' (setf nums (bst-remove 5 nums #'
> (bst-traverse #'princ nums)
13246789

(I wrote this article to help myself understand exactly what McCarthy discovered. You don't need to know this stuff to program in Lisp, but it should be helpful to anyone who wants to understand the essence of Lisp-- both in the sense of its origins and its semantic core. The fact that it has such a core is one of Lisp's distinguishing features, and the reason why, unlike other languages, Lisp has dialects.)

In 1960, John McCarthy published a remarkable paper in which he did for programming something like what Euclid did for geometry. He showed how, given a handful of simple operators and a notation for functions, you can build a whole programming language. He called this language Lisp, for "List Processing," because one of his key ideas was to use a simple data structure called a list for both code and data.

It's worth understanding what McCarthy discovered, not just as a landmark in the history of computers, but as a model for what programming is tending to become in our own time. It seems to me that there have been two really clean, consistent models of programming so far: the C model and the Lisp model. These two seem points of high ground, with swampy lowlands between them. As computers have grown more powerful, the new languages being developed have been moving steadily toward the Lisp model. A popular recipe for new programming languages in the past 20 years has been to take the C model of computing and add to it, piecemeal, parts taken from the Lisp model, like runtime typing and garbage collection.

In this article I'm going to try to explain in the simplest possible terms what McCarthy discovered. The point is not just to learn about an interesting theoretical result someone figured out forty years ago, but to show where languages are heading. The unusual thing about Lisp-- in fact, the defining quality of Lisp-- is that it can be written in itself. To understand what McCarthy meant by this, we're going to retrace his steps, with his mathematical notation translated into running Common Lisp code.

Want to start a startup? Get funded by Y Combinator.

July 2013

One of the most common types of advice we give at Y Combinator is to do things that don't scale. A lot of would-be founders believe that startups either take off or don't. You build something, make it available, and if you've made a better mousetrap, people beat a path to your door as promised. Or they don't, in which case the market must not exist. [1]

Actually startups take off because the founders make them take off. There may be a handful that just grew by themselves, but usually it takes some sort of push to get them going. A good metaphor would be the cranks that car engines had before they got electric starters. Once the engine was going, it would keep going, but there was a separate and laborious process to get it going.

Recruit

The most common unscalable thing founders have to do at the start is to recruit users manually. Nearly all startups have to. You can't wait for users to come to you. You have to go out and get them.

Stripe is one of the most successful startups we've funded, and the problem they solved was an urgent one. If anyone could have sat back and waited for users, it was Stripe. But in fact they're famous within YC for aggressive early user acquisition.

Startups building things for other startups have a big pool of potential users in the other companies we've funded, and none took better advantage of it than Stripe. At YC we use the term "Collison installation" for the technique they invented. More diffident founders ask "Will you try our beta?" and if the answer is yes, they say "Great, we'll send you a link." But the Collison brothers weren't going to wait. When anyone agreed to try Stripe they'd say "Right then, give me your laptop" and set them up on the spot.

There are two reasons founders resist going out and recruiting users individually. One is a combination of shyness and laziness. They'd rather sit at home writing code than go out and talk to a bunch of strangers and probably be rejected by most of them. But for a startup to succeed, at least one founder (usually the CEO) will have to spend a lot of time on sales and marketing. [2]

The other reason founders ignore this path is that the absolute numbers seem so small at first. This can't be how the big, famous startups got started, they think. The mistake they make is to underestimate the power of compound growth. We encourage every startup to measure their progress by weekly growth rate. If you have 100 users, you need to get 10 more next week to grow 10% a week. And while 110 may not seem much better than 100, if you keep growing at 10% a week you'll be surprised how big the numbers get. After a year you'll have 14,000 users, and after 2 years you'll have 2 million.

You'll be doing different things when you're acquiring users a thousand at a time, and growth has to slow down eventually. But if the market exists you can usually start by recruiting users manually and then gradually switch to less manual methods. [3]

Airbnb is a classic example of this technique. Marketplaces are so hard to get rolling that you should expect to take heroic measures at first. In Airbnb's case, these consisted of going door to door in New York, recruiting new users and helping existing ones improve their listings. When I remember the Airbnbs during YC, I picture them with rolly bags, because when they showed up for tuesday dinners they'd always just flown back from somewhere.

Fragile

Airbnb now seems like an unstoppable juggernaut, but early on it was so fragile that about 30 days of going out and engaging in person with users made the difference between success and failure.

That initial fragility was not a unique feature of Airbnb. Almost all startups are fragile initially. And that's one of the biggest things inexperienced founders and investors (and reporters and know-it-alls on forums) get wrong about them. They unconsciously judge larval startups by the standards of established ones. They're like someone looking at a newborn baby and concluding "there's no way this tiny creature could ever accomplish anything."

It's harmless if reporters and know-it-alls dismiss your startup. They always get things wrong. It's even ok if investors dismiss your startup; they'll change their minds when they see growth. The big danger is that you'll dismiss your startup yourself. I've seen it happen. I often have to encourage founders who don't see the full potential of what they're building. Even Bill Gates made that mistake. He returned to Harvard for the fall semester after starting Microsoft. He didn't stay long, but he wouldn't have returned at all if he'd realized Microsoft was going to be even a fraction of the size it turned out to be. [4]

The question to ask about an early stage startup is not "is this company taking over the world?" but "how big could this company get if the founders did the right things?" And the right things often seem both laborious and inconsequential at the time. Microsoft can't have seemed very impressive when it was just a couple guys in Albuquerque writing Basic interpreters for a market of a few thousand hobbyists (as they were then called), but in retrospect that was the optimal path to dominating microcomputer software. And I know Brian Chesky and Joe Gebbia didn't feel like they were en route to the big time as they were taking "professional" photos of their first hosts' apartments. They were just trying to survive. But in retrospect that too was the optimal path to dominating a big market.

How do you find users to recruit manually? If you build something to solve your own problems, then you only have to find your peers, which is usually straightforward. Otherwise you'll have to make a more deliberate effort to locate the most promising vein of users. The usual way to do that is to get some initial set of users by doing a comparatively untargeted launch, and then to observe which kind seem most enthusiastic, and seek out more like them. For example, Ben Silbermann noticed that a lot of the earliest Pinterest users were interested in design, so he went to a conference of design bloggers to recruit users, and that worked well. [5]

Delight

You should take extraordinary measures not just to acquire users, but also to make them happy. For as long as they could (which turned out to be surprisingly long), Wufoo sent each new user a hand-written thank you note. Your first users should feel that signing up with you was one of the best choices they ever made. And you in turn should be racking your brains to think of new ways to delight them.

Why do we have to teach startups this? Why is it counterintuitive for founders? Three reasons, I think.

One is that a lot of of startup founders are trained as engineers, and customer service is not part of the training of engineers. You're supposed to build things that are robust and elegant, not be slavishly attentive to individual users like some kind of salesperson. Ironically, part of the reason engineering is traditionally averse to handholding is that its traditions date from a time when engineers were less powerful—when they were only in charge of their narrow domain of building things, rather than running the whole show. You can be ornery when you're Scotty, but not when you're Kirk.

Another reason founders don't focus enough on individual customers is that they worry it won't scale. But when founders of larval startups worry about this, I point out that in their current state they have nothing to lose. Maybe if they go out of their way to make existing users super happy, they'll one day have too many to do so much for. That would be a great problem to have. See if you can make it happen. And incidentally, when it does, you'll find that delighting customers scales better than you expected. Partly because you can usually find ways to make anything scale more than you would have predicted, and partly because delighting customers will by then have permeated your culture.

I have never once seen a startup lured down a blind alley by trying too hard to make their initial users happy.

But perhaps the biggest thing preventing founders from realizing how attentive they could be to their users is that they've never experienced such attention themselves. Their standards for customer service have been set by the companies they've been customers of, which are mostly big ones. Tim Cook doesn't send you a hand-written note after you buy a laptop. He can't. But you can. That's one advantage of being small: you can provide a level of service no big company can. [6]

Once you realize that existing conventions are not the upper bound on user experience, it's interesting in a very pleasant way to think about how far you could go to delight your users.

Experience

I was trying to think of a phrase to convey how extreme your attention to users should be, and I realized Steve Jobs had already done it: insanely great. Steve wasn't just using "insanely" as a synonym for "very." He meant it more literally—that one should focus on quality of execution to a degree that in everyday life would be considered pathological.

All the most successful startups we've funded have, and that probably doesn't surprise would-be founders. What novice founders don't get is what insanely great translates to in a larval startup. When Steve Jobs started using that phrase, Apple was already an established company. He meant the Mac (and its documentation and even packaging—such is the nature of obsession) should be insanely well designed and manufactured. That's not hard for engineers to grasp. It's just a more extreme version of designing a robust and elegant product.

What founders have a hard time grasping (and Steve himself might have had a hard time grasping) is what insanely great morphs into as you roll the time slider back to the first couple months of a startup's life. It's not the product that should be insanely great, but the experience of being your user. The product is just one component of that. For a big company it's necessarily the dominant one. But you can and should give users an insanely great experience with an early, incomplete, buggy product, if you make up the difference with attentiveness.

Can, perhaps, but should? Yes. Over-engaging with early users is not just a permissible technique for getting growth rolling. For most successful startups it's a necessary part of the feedback loop that makes the product good. Making a better mousetrap is not an atomic operation. Even if you start the way most successful startups have, by building something you yourself need, the first thing you build is never quite right. And except in domains with big penalties for making mistakes, it's often better not to aim for perfection initially. In software, especially, it usually works best to get something in front of users as soon as it has a quantum of utility, and then see what they do with it. Perfectionism is often an excuse for procrastination, and in any case your initial model of users is always inaccurate, even if you're one of them. [7]

The feedback you get from engaging directly with your earliest users will be the best you ever get. When you're so big you have to resort to focus groups, you'll wish you could go over to your users' homes and offices and watch them use your stuff like you did when there were only a handful of them.

Fire

Sometimes the right unscalable trick is to focus on a deliberately narrow market. It's like keeping a fire contained at first to get it really hot before adding more logs.

That's what Facebook did. At first it was just for Harvard students. In that form it only had a potential market of a few thousand people, but because they felt it was really for them, a critical mass of them signed up. After Facebook stopped being for Harvard students, it remained for students at specific colleges for quite a while. When I interviewed Mark Zuckerberg at Startup School, he said that while it was a lot of work creating course lists for each school, doing that made students feel the site was their natural home.

Any startup that could be described as a marketplace usually has to start in a subset of the market, but this can work for other startups as well. It's always worth asking if there's a subset of the market in which you can get a critical mass of users quickly. [8]

Most startups that use the contained fire strategy do it unconsciously. They build something for themselves and their friends, who happen to be the early adopters, and only realize later that they could offer it to a broader market. The strategy works just as well if you do it unconsciously. The biggest danger of not being consciously aware of this pattern is for those who naively discard part of it. E.g. if you don't build something for yourself and your friends, or even if you do, but you come from the corporate world and your friends are not early adopters, you'll no longer have a perfect initial market handed to you on a platter.

Among companies, the best early adopters are usually other startups. They're more open to new things both by nature and because, having just been started, they haven't made all their choices yet. Plus when they succeed they grow fast, and you with them. It was one of many unforeseen advantages of the YC model (and specifically of making YC big) that B2B startups now have an instant market of hundreds of other startups ready at hand.

Meraki

For hardware startups there's a variant of doing things that don't scale that we call "pulling a Meraki." Although we didn't fund Meraki, the founders were Robert Morris's grad students, so we know their history. They got started by doing something that really doesn't scale: assembling their routers themselves.

Hardware startups face an obstacle that software startups don't. The minimum order for a factory production run is usually several hundred thousand dollars. Which can put you in a catch-22: without a product you can't generate the growth you need to raise the money to manufacture your product. Back when hardware startups had to rely on investors for money, you had to be pretty convincing to overcome this. The arrival of crowdfunding (or more precisely, preorders) has helped a lot. But even so I'd advise startups to pull a Meraki initially if they can. That's what Pebble did. The Pebbles assembled the first several hundred watches themselves. If they hadn't gone through that phase, they probably wouldn't have sold $10 million worth of watches when they did go on Kickstarter.

Like paying excessive attention to early customers, fabricating things yourself turns out to be valuable for hardware startups. You can tweak the design faster when you're the factory, and you learn things you'd never have known otherwise. Eric Migicovsky of Pebble said one of things he learned was "how valuable it was to source good screws." Who knew?

Consult

Sometimes we advise founders of B2B startups to take over-engagement to an extreme, and to pick a single user and act as if they were consultants building something just for that one user. The initial user serves as the form for your mold; keep tweaking till you fit their needs perfectly, and you'll usually find you've made something other users want too. Even if there aren't many of them, there are probably adjacent territories that have more. As long as you can find just one user who really needs something and can act on that need, you've got a toehold in making something people want, and that's as much as any startup needs initially. [9]

Consulting is the canonical example of work that doesn't scale. But (like other ways of bestowing one's favors liberally) it's safe to do it so long as you're not being paid to. That's where companies cross the line. So long as you're a product company that's merely being extra attentive to a customer, they're very grateful even if you don't solve all their problems. But when they start paying you specifically for that attentiveness—when they start paying you by the hour—they expect you to do everything.

Another consulting-like technique for recruiting initially lukewarm users is to use your software yourselves on their behalf. We did that at Viaweb. When we approached merchants asking if they wanted to use our software to make online stores, some said no, but they'd let us make one for them. Since we would do anything to get users, we did. We felt pretty lame at the time. Instead of organizing big strategic e-commerce partnerships, we were trying to sell luggage and pens and men's shirts. But in retrospect it was exactly the right thing to do, because it taught us how it would feel to merchants to use our software. Sometimes the feedback loop was near instantaneous: in the middle of building some merchant's site I'd find I needed a feature we didn't have, so I'd spend a couple hours implementing it and then resume building the site.

Manual

There's a more extreme variant where you don't just use your software, but are your software. When you only have a small number of users, you can sometimes get away with doing by hand things that you plan to automate later. This lets you launch faster, and when you do finally automate yourself out of the loop, you'll know exactly what to build because you'll have muscle memory from doing it yourself.

When manual components look to the user like software, this technique starts to have aspects of a practical joke. For example, the way Stripe delivered "instant" merchant accounts to its first users was that the founders manually signed them up for traditional merchant accounts behind the scenes.

Some startups could be entirely manual at first. If you can find someone with a problem that needs solving and you can solve it manually, go ahead and do that for as long as you can, and then gradually automate the bottlenecks. It would be a little frightening to be solving users' problems in a way that wasn't yet automatic, but less frightening than the far more common case of having something automatic that doesn't yet solve anyone's problems.

Big

I should mention one sort of initial tactic that usually doesn't work: the Big Launch. I occasionally meet founders who seem to believe startups are projectiles rather than powered aircraft, and that they'll make it big if and only if they're launched with sufficient initial velocity. They want to launch simultaneously in 8 different publications, with embargoes. And on a tuesday, of course, since they read somewhere that's the optimum day to launch something.

It's easy to see how little launches matter. Think of some successful startups. How many of their launches do you remember? All you need from a launch is some initial core of users. How well you're doing a few months later will depend more on how happy you made those users than how many there were of them. [10]

So why do founders think launches matter? A combination of solipsism and laziness. They think what they're building is so great that everyone who hears about it will immediately sign up. Plus it would be so much less work if you could get users merely by broadcasting your existence, rather than recruiting them one at a time. But even if what you're building really is great, getting users will always be a gradual process—partly because great things are usually also novel, but mainly because users have other things to think about.

Partnerships too usually don't work. They don't work for startups in general, but they especially don't work as a way to get growth started. It's a common mistake among inexperienced founders to believe that a partnership with a big company will be their big break. Six months later they're all saying the same thing: that was way more work than we expected, and we ended up getting practically nothing out of it. [11]

It's not enough just to do something extraordinary initially. You have to make an extraordinary effort initially. Any strategy that omits the effort—whether it's expecting a big launch to get you users, or a big partner—is ipso facto suspect.

Vector

The need to do something unscalably laborious to get started is so nearly universal that it might be a good idea to stop thinking of startup ideas as scalars. Instead we should try thinking of them as pairs of what you're going to build, plus the unscalable thing(s) you're going to do initially to get the company going.

It could be interesting to start viewing startup ideas this way, because now that there are two components you can try to be imaginative about the second as well as the first. But in most cases the second component will be what it usually is—recruit users manually and give them an overwhelmingly good experience—and the main benefit of treating startups as vectors will be to remind founders they need to work hard in two dimensions. [12]

In the best case, both components of the vector contribute to your company's DNA: the unscalable things you have to do to get started are not merely a necessary evil, but change the company permanently for the better. If you have to be aggressive about user acquisition when you're small, you'll probably still be aggressive when you're big. If you have to manufacture your own hardware, or use your software on users's behalf, you'll learn things you couldn't have learned otherwise. And most importantly, if you have to work hard to delight users when you only have a handful of them, you'll keep doing it when you have a lot.







Notes

[1] Actually Emerson never mentioned mousetraps specifically. He wrote "If a man has good corn or wood, or boards, or pigs, to sell, or can make better chairs or knives, crucibles or church organs, than anybody else, you will find a broad hard-beaten road to his house, though it be in the woods."

[2] Thanks to Sam Altman for suggesting I make this explicit. And no, you can't avoid doing sales by hiring someone to do it for you. You have to do sales yourself initially. Later you can hire a real salesperson to replace you.

[3] The reason this works is that as you get bigger, your size helps you grow. Patrick Collison wrote "At some point, there was a very noticeable change in how Stripe felt. It tipped from being this boulder we had to push to being a train car that in fact had its own momentum."

[4] One of the more subtle ways in which YC can help founders is by calibrating their ambitions, because we know exactly how a lot of successful startups looked when they were just getting started.

[5] If you're building something for which you can't easily get a small set of users to observe—e.g. enterprise software—and in a domain where you have no connections, you'll have to rely on cold calls and introductions. But should you even be working on such an idea?

[6] Garry Tan pointed out an interesting trap founders fall into in the beginning. They want so much to seem big that they imitate even the flaws of big companies, like indifference to individual users. This seems to them more "professional." Actually it's better to embrace the fact that you're small and use whatever advantages that brings.

[7] Your user model almost couldn't be perfectly accurate, because users' needs often change in response to what you build for them. Build them a microcomputer, and suddenly they need to run spreadsheets on it, because the arrival of your new microcomputer causes someone to invent the spreadsheet.

[8] If you have to choose between the subset that will sign up quickest and those that will pay the most, it's usually best to pick the former, because those are probably the early adopters. They'll have a better influence on your product, and they won't make you expend as much effort on sales. And though they have less money, you don't need that much to maintain your target growth rate early on.

[9] Yes, I can imagine cases where you could end up making something that was really only useful for one user. But those are usually obvious, even to inexperienced founders. So if it's not obvious you'd be making something for a market of one, don't worry about that danger.

[10] There may even be an inverse correlation between launch magnitude and success. The only launches I remember are famous flops like the Segway and Google Wave. Wave is a particularly alarming example, because I think it was actually a great idea that was killed partly by its overdone launch.

[11] Google grew big on the back of Yahoo, but that wasn't a partnership. Yahoo was their customer.

[12] It will also remind founders that an idea where the second component is empty—an idea where there is nothing you can do to get going, e.g. because you have no way to find users to recruit manually—is probably a bad idea, at least for those founders.

Thanks to Sam Altman, Paul Buchheit, Patrick Collison, Kevin Hale, Steven Levy, Jessica Livingston, Geoff Ralston, and Garry Tan for reading drafts of this.

(This entry from the Jargon File, which later became the Hackers' Dictionary, originally dates from the mid-80s. The first versions of the Jargon File didn't have an entry for Lisp, because it was assumed that every hacker knew what it was.)

:LISP: /n./ [from `LISt Processing language', but mythically from `Lots of Irritating Superfluous Parentheses'] AI's mother tongue, a language based on the ideas of (a) variable-length lists and trees as fundamental data types, and (b) the interpretation of code as data and vice-versa. Invented by John McCarthy at MIT in the late 1950s, it is actually older than any other {HLL} still in use except FORTRAN. Accordingly, it has undergone considerable adaptive radiation over the years; modern variants are quite different in detail from the original LISP 1.5. The dominant HLL among hackers until the early 1980s, LISP now shares the throne with {C}. See {languages of choice}.

All LISP functions and programs are expressions that return values; this, together with the high memory utilization of LISPs, gave rise to Alan Perlis's famous quip (itself a take on an Oscar Wilde quote) that "LISP programmers know the value of everything and the cost of nothing".

One significant application for LISP has been as a proof by example that most newer languages, such as {COBOL} and {Ada}, are full of unnecessary {crock}s. When the {Right Thing} has already been done once, there is no justification for {bogosity} in newer languages.

1. The company is spending more now than it did the first time it raised money.
   
   
2. Investors have much higher standards for companies that have already raised money.
   
   
3. The company is now starting to read as a failure. The first time it raised money, it was neither a success nor a failure; it was too early to ask. Now it's possible to ask that question, and the default answer is failure, because that is at this point the default outcome.

We're really excited about your project, and we want to keep in close touch as you develop it further.

Want to start a startup? Get funded by Y Combinator.

October 2010

After barely changing at all for decades, the startup funding business is now in what could, at least by comparison, be called turmoil. At Y Combinator we've seen dramatic changes in the funding environment for startups. Fortunately one of them is much higher valuations.

The trends we've been seeing are probably not YC-specific. I wish I could say they were, but the main cause is probably just that we see trends first—partly because the startups we fund are very plugged into the Valley and are quick to take advantage of anything new, and partly because we fund so many that we have enough data points to see patterns clearly.

What we're seeing now, everyone's probably going to be seeing in the next couple years. So I'm going to explain what we're seeing, and what that will mean for you if you try to raise money.

Super-Angels

Let me start by describing what the world of startup funding used to look like. There used to be two sharply differentiated types of investors: angels and venture capitalists. Angels are individual rich people who invest small amounts of their own money, while VCs are employees of funds that invest large amounts of other people's.

For decades there were just those two types of investors, but now a third type has appeared halfway between them: the so-called super-angels. [1] And VCs have been provoked by their arrival into making a lot of angel-style investments themselves. So the previously sharp line between angels and VCs has become hopelessly blurred.

There used to be a no man's land between angels and VCs. Angels would invest $20k to $50k apiece, and VCs usually a million or more. So an angel round meant a collection of angel investments that combined to maybe $200k, and a VC round meant a series A round in which a single VC fund (or occasionally two) invested $1-5 million.

The no man's land between angels and VCs was a very inconvenient one for startups, because it coincided with the amount many wanted to raise. Most startups coming out of Demo Day wanted to raise around $400k. But it was a pain to stitch together that much out of angel investments, and most VCs weren't interested in investments so small. That's the fundamental reason the super-angels have appeared. They're responding to the market.

The arrival of a new type of investor is big news for startups, because there used to be only two and they rarely competed with one another. Super-angels compete with both angels and VCs. That's going to change the rules about how to raise money. I don't know yet what the new rules will be, but it looks like most of the changes will be for the better.

A super-angel has some of the qualities of an angel, and some of the qualities of a VC. They're usually individuals, like angels. In fact many of the current super-angels were initially angels of the classic type. But like VCs, they invest other people's money. This allows them to invest larger amounts than angels: a typical super-angel investment is currently about $100k. They make investment decisions quickly, like angels. And they make a lot more investments per partner than VCs—up to 10 times as many.

The fact that super-angels invest other people's money makes them doubly alarming to VCs. They don't just compete for startups; they also compete for investors. What super-angels really are is a new form of fast-moving, lightweight VC fund. And those of us in the technology world know what usually happens when something comes along that can be described in terms like that. Usually it's the replacement.

Will it be? As of now, few of the startups that take money from super-angels are ruling out taking VC money. They're just postponing it. But that's still a problem for VCs. Some of the startups that postpone raising VC money may do so well on the angel money they raise that they never bother to raise more. And those who do raise VC rounds will be able to get higher valuations when they do. If the best startups get 10x higher valuations when they raise series A rounds, that would cut VCs' returns from winners at least tenfold. [2]

So I think VC funds are seriously threatened by the super-angels. But one thing that may save them to some extent is the uneven distribution of startup outcomes: practically all the returns are concentrated in a few big successes. The expected value of a startup is the percentage chance it's Google. So to the extent that winning is a matter of absolute returns, the super-angels could win practically all the battles for individual startups and yet lose the war, if they merely failed to get those few big winners. And there's a chance that could happen, because the top VC funds have better brands, and can also do more for their portfolio companies. [3]

Because super-angels make more investments per partner, they have less partner per investment. They can't pay as much attention to you as a VC on your board could. How much is that extra attention worth? It will vary enormously from one partner to another. There's no consensus yet in the general case. So for now this is something startups are deciding individually.

Till now, VCs' claims about how much value they added were sort of like the government's. Maybe they made you feel better, but you had no choice in the matter, if you needed money on the scale only VCs could supply. Now that VCs have competitors, that's going to put a market price on the help they offer. The interesting thing is, no one knows yet what it will be.

Do startups that want to get really big need the sort of advice and connections only the top VCs can supply? Or would super-angel money do just as well? The VCs will say you need them, and the super-angels will say you don't. But the truth is, no one knows yet, not even the VCs and super-angels themselves. All the super-angels know is that their new model seems promising enough to be worth trying, and all the VCs know is that it seems promising enough to worry about.

Rounds

Whatever the outcome, the conflict between VCs and super-angels is good news for founders. And not just for the obvious reason that more competition for deals means better terms. The whole shape of deals is changing.

One of the biggest differences between angels and VCs is the amount of your company they want. VCs want a lot. In a series A round they want a third of your company, if they can get it. They don't care much how much they pay for it, but they want a lot because the number of series A investments they can do is so small. In a traditional series A investment, at least one partner from the VC fund takes a seat on your board. [4] Since board seats last about 5 years and each partner can't handle more than about 10 at once, that means a VC fund can only do about 2 series A deals per partner per year. And that means they need to get as much of the company as they can in each one. You'd have to be a very promising startup indeed to get a VC to use up one of his 10 board seats for only a few percent of you.

Since angels generally don't take board seats, they don't have this constraint. They're happy to buy only a few percent of you. And although the super-angels are in most respects mini VC funds, they've retained this critical property of angels. They don't take board seats, so they don't need a big percentage of your company.

Though that means you'll get correspondingly less attention from them, it's good news in other respects. Founders never really liked giving up as much equity as VCs wanted. It was a lot of the company to give up in one shot. Most founders doing series A deals would prefer to take half as much money for half as much stock, and then see what valuation they could get for the second half of the stock after using the first half of the money to increase its value. But VCs never offered that option.

Now startups have another alternative. Now it's easy to raise angel rounds about half the size of series A rounds. Many of the startups we fund are taking this route, and I predict that will be true of startups in general.

A typical big angel round might be $600k on a convertible note with a valuation cap of $4 million premoney. Meaning that when the note converts into stock (in a later round, or upon acquisition), the investors in that round will get .6 / 4.6, or 13% of the company. That's a lot less than the 30 to 40% of the company you usually give up in a series A round if you do it so early. [5]

But the advantage of these medium-sized rounds is not just that they cause less dilution. You also lose less control. After an angel round, the founders almost always still have control of the company, whereas after a series A round they often don't. The traditional board structure after a series A round is two founders, two VCs, and a (supposedly) neutral fifth person. Plus series A terms usually give the investors a veto over various kinds of important decisions, including selling the company. Founders usually have a lot of de facto control after a series A, as long as things are going well. But that's not the same as just being able to do what you want, like you could before.

A third and quite significant advantage of angel rounds is that they're less stressful to raise. Raising a traditional series A round has in the past taken weeks, if not months. When a VC firm can only do 2 deals per partner per year, they're careful about which they do. To get a traditional series A round you have to go through a series of meetings, culminating in a full partner meeting where the firm as a whole says yes or no. That's the really scary part for founders: not just that series A rounds take so long, but at the end of this long process the VCs might still say no. The chance of getting rejected after the full partner meeting averages about 25%. At some firms it's over 50%.

Fortunately for founders, VCs have been getting a lot faster. Nowadays Valley VCs are more likely to take 2 weeks than 2 months. But they're still not as fast as angels and super-angels, the most decisive of whom sometimes decide in hours.

Raising an angel round is not only quicker, but you get feedback as it progresses. An angel round is not an all or nothing thing like a series A. It's composed of multiple investors with varying degrees of seriousness, ranging from the upstanding ones who commit unequivocally to the jerks who give you lines like "come back to me to fill out the round." You usually start collecting money from the most committed investors and work your way out toward the ambivalent ones, whose interest increases as the round fills up.

But at each point you know how you're doing. If investors turn cold you may have to raise less, but when investors in an angel round turn cold the process at least degrades gracefully, instead of blowing up in your face and leaving you with nothing, as happens if you get rejected by a VC fund after a full partner meeting. Whereas if investors seem hot, you can not only close the round faster, but now that convertible notes are becoming the norm, actually raise the price to reflect demand.

Valuation

However, the VCs have a weapon they can use against the super-angels, and they have started to use it. VCs have started making angel-sized investments too. The term "angel round" doesn't mean that all the investors in it are angels; it just describes the structure of the round. Increasingly the participants include VCs making investments of a hundred thousand or two. And when VCs invest in angel rounds they can do things that super-angels don't like. VCs are quite valuation-insensitive in angel rounds—partly because they are in general, and partly because they don't care that much about the returns on angel rounds, which they still view mostly as a way to recruit startups for series A rounds later. So VCs who invest in angel rounds can blow up the valuations for angels and super-angels who invest in them. [6]

Some super-angels seem to care about valuations. Several turned down YC-funded startups after Demo Day because their valuations were too high. This was not a problem for the startups; by definition a high valuation means enough investors were willing to accept it. But it was mysterious to me that the super-angels would quibble about valuations. Did they not understand that the big returns come from a few big successes, and that it therefore mattered far more which startups you picked than how much you paid for them?

After thinking about it for a while and observing certain other signs, I have a theory that explains why the super-angels may be smarter than they seem. It would make sense for super-angels to want low valuations if they're hoping to invest in startups that get bought early. If you're hoping to hit the next Google, you shouldn't care if the valuation is 20 million. But if you're looking for companies that are going to get bought for 30 million, you care. If you invest at 20 and the company gets bought for 30, you only get 1.5x. You might as well buy Apple.

So if some of the super-angels were looking for companies that could get acquired quickly, that would explain why they'd care about valuations. But why would they be looking for those? Because depending on the meaning of "quickly," it could actually be very profitable. A company that gets acquired for 30 million is a failure to a VC, but it could be a 10x return for an angel, and moreover, a quick 10x return. Rate of return is what matters in investing—not the multiple you get, but the multiple per year. If a super-angel gets 10x in one year, that's a higher rate of return than a VC could ever hope to get from a company that took 6 years to go public. To get the same rate of return, the VC would have to get a multiple of 10^6—one million x. Even Google didn't come close to that.

So I think at least some super-angels are looking for companies that will get bought. That's the only rational explanation for focusing on getting the right valuations, instead of the right companies. And if so they'll be different to deal with than VCs. They'll be tougher on valuations, but more accommodating if you want to sell early.

Prognosis

Who will win, the super-angels or the VCs? I think the answer to that is, some of each. They'll each become more like one another. The super-angels will start to invest larger amounts, and the VCs will gradually figure out ways to make more, smaller investments faster. A decade from now the players will be hard to tell apart, and there will probably be survivors from each group.

What does that mean for founders? One thing it means is that the high valuations startups are presently getting may not last forever. To the extent that valuations are being driven up by price-insensitive VCs, they'll fall again if VCs become more like super-angels and start to become more miserly about valuations. Fortunately if this does happen it will take years.

The short term forecast is more competition between investors, which is good news for you. The super-angels will try to undermine the VCs by acting faster, and the VCs will try to undermine the super-angels by driving up valuations. Which for founders will result in the perfect combination: funding rounds that close fast, with high valuations.

But remember that to get that combination, your startup will have to appeal to both super-angels and VCs. If you don't seem like you have the potential to go public, you won't be able to use VCs to drive up the valuation of an angel round.

There is a danger of having VCs in an angel round: the so-called signalling risk. If VCs are only doing it in the hope of investing more later, what happens if they don't? That's a signal to everyone else that they think you're lame.

How much should you worry about that? The seriousness of signalling risk depends on how far along you are. If by the next time you need to raise money, you have graphs showing rising revenue or traffic month after month, you don't have to worry about any signals your existing investors are sending. Your results will speak for themselves. [7]

Whereas if the next time you need to raise money you won't yet have concrete results, you may need to think more about the message your investors might send if they don't invest more. I'm not sure yet how much you have to worry, because this whole phenomenon of VCs doing angel investments is so new. But my instincts tell me you don't have to worry much. Signalling risk smells like one of those things founders worry about that's not a real problem. As a rule, the only thing that can kill a good startup is the startup itself. Startups hurt themselves way more often than competitors hurt them, for example. I suspect signalling risk is in this category too.

One thing YC-funded startups have been doing to mitigate the risk of taking money from VCs in angel rounds is not to take too much from any one VC. Maybe that will help, if you have the luxury of turning down money.

Fortunately, more and more startups will. After decades of competition that could best be described as intramural, the startup funding business is finally getting some real competition. That should last several years at least, and maybe a lot longer. Unless there's some huge market crash, the next couple years are going to be a good time for startups to raise money. And that's exciting because it means lots more startups will happen.







Notes

[1] I've also heard them called "Mini-VCs" and "Micro-VCs." I don't know which name will stick.

There were a couple predecessors. Ron Conway had angel funds starting in the 1990s, and in some ways First Round Capital is closer to a super-angel than a VC fund.

[2] It wouldn't cut their overall returns tenfold, because investing later would probably (a) cause them to lose less on investments that failed, and (b) not allow them to get as large a percentage of startups as they do now. So it's hard to predict precisely what would happen to their returns.

[3] The brand of an investor derives mostly from the success of their portfolio companies. The top VCs thus have a big brand advantage over the super-angels. They could make it self-perpetuating if they used it to get all the best new startups. But I don't think they'll be able to. To get all the best startups, you have to do more than make them want you. You also have to want them; you have to recognize them when you see them, and that's much harder. Super-angels will snap up stars that VCs miss. And that will cause the brand gap between the top VCs and the super-angels gradually to erode.

[4] Though in a traditional series A round VCs put two partners on your board, there are signs now that VCs may begin to conserve board seats by switching to what used to be considered an angel-round board, consisting of two founders and one VC. Which is also to the founders' advantage if it means they still control the company.

[5] In a series A round, you usually have to give up more than the actual amount of stock the VCs buy, because they insist you dilute yourselves to set aside an "option pool" as well. I predict this practice will gradually disappear though.

[6] The best thing for founders, if they can get it, is a convertible note with no valuation cap at all. In that case the money invested in the angel round just converts into stock at the valuation of the next round, no matter how large. Angels and super-angels tend not to like uncapped notes. They have no idea how much of the company they're buying. If the company does well and the valuation of the next round is high, they may end up with only a sliver of it. So by agreeing to uncapped notes, VCs who don't care about valuations in angel rounds can make offers that super-angels hate to match.

[7] Obviously signalling risk is also not a problem if you'll never need to raise more money. But startups are often mistaken about that.

Thanks to Sam Altman, John Bautista, Patrick Collison, James Lindenbaum, Reid Hoffman, Jessica Livingston and Harj Taggar for reading drafts of this.

Want to start a startup? Get funded by Y Combinator.

June 2006

(This essay is derived from talks at Usenix 2006 and Railsconf 2006.)

A couple years ago my friend Trevor and I went to look at the Apple garage. As we stood there, he said that as a kid growing up in Saskatchewan he'd been amazed at the dedication Jobs and Wozniak must have had to work in a garage. "Those guys must have been freezing!"

That's one of California's hidden advantages: the mild climate means there's lots of marginal space. In cold places that margin gets trimmed off. There's a sharper line between outside and inside, and only projects that are officially sanctioned—by organizations, or parents, or wives, or at least by oneself—get proper indoor space. That raises the activation energy for new ideas. You can't just tinker. You have to justify.

Some of Silicon Valley's most famous companies began in garages: Hewlett-Packard in 1938, Apple in 1976, Google in 1998. In Apple's case the garage story is a bit of an urban legend. Woz says all they did there was assemble some computers, and that he did all the actual design of the Apple I and Apple II in his apartment or his cube at HP. [1] This was apparently too marginal even for Apple's PR people.

By conventional standards, Jobs and Wozniak were marginal people too. Obviously they were smart, but they can't have looked good on paper. They were at the time a pair of college dropouts with about three years of school between them, and hippies to boot. Their previous business experience consisted of making "blue boxes" to hack into the phone system, a business with the rare distinction of being both illegal and unprofitable.

Outsiders

Now a startup operating out of a garage in Silicon Valley would feel part of an exalted tradition, like the poet in his garret, or the painter who can't afford to heat his studio and thus has to wear a beret indoors. But in 1976 it didn't seem so cool. The world hadn't yet realized that starting a computer company was in the same category as being a writer or a painter. It hadn't been for long. Only in the preceding couple years had the dramatic fall in the cost of hardware allowed outsiders to compete.

In 1976, everyone looked down on a company operating out of a garage, including the founders. One of the first things Jobs did when they got some money was to rent office space. He wanted Apple to seem like a real company.

They already had something few real companies ever have: a fabulously well designed product. You'd think they'd have had more confidence. But I've talked to a lot of startup founders, and it's always this way. They've built something that's going to change the world, and they're worried about some nit like not having proper business cards.

That's the paradox I want to explore: great new things often come from the margins, and yet the people who discover them are looked down on by everyone, including themselves.

It's an old idea that new things come from the margins. I want to examine its internal structure. Why do great ideas come from the margins? What kind of ideas? And is there anything we can do to encourage the process?

Insiders

One reason so many good ideas come from the margin is simply that there's so much of it. There have to be more outsiders than insiders, if insider means anything. If the number of outsiders is huge it will always seem as if a lot of ideas come from them, even if few do per capita. But I think there's more going on than this. There are real disadvantages to being an insider, and in some kinds of work they can outweigh the advantages.

Imagine, for example, what would happen if the government decided to commission someone to write an official Great American Novel. First there'd be a huge ideological squabble over who to choose. Most of the best writers would be excluded for having offended one side or the other. Of the remainder, the smart ones would refuse such a job, leaving only a few with the wrong sort of ambition. The committee would choose one at the height of his career—that is, someone whose best work was behind him—and hand over the project with copious free advice about how the book should show in positive terms the strength and diversity of the American people, etc, etc.

The unfortunate writer would then sit down to work with a huge weight of expectation on his shoulders. Not wanting to blow such a public commission, he'd play it safe. This book had better command respect, and the way to ensure that would be to make it a tragedy. Audiences have to be enticed to laugh, but if you kill people they feel obliged to take you seriously. As everyone knows, America plus tragedy equals the Civil War, so that's what it would have to be about. Better stick to the standard cartoon version that the Civil War was about slavery; people would be confused otherwise; plus you can show a lot of strength and diversity. When finally completed twelve years later, the book would be a 900-page pastiche of existing popular novels—roughly Gone with the Wind plus Roots. But its bulk and celebrity would make it a bestseller for a few months, until blown out of the water by a talk-show host's autobiography. The book would be made into a movie and thereupon forgotten, except by the more waspish sort of reviewers, among whom it would be a byword for bogusness like Milli Vanilli or Battlefield Earth.

Maybe I got a little carried away with this example. And yet is this not at each point the way such a project would play out? The government knows better than to get into the novel business, but in other fields where they have a natural monopoly, like nuclear waste dumps, aircraft carriers, and regime change, you'd find plenty of projects isomorphic to this one—and indeed, plenty that were less successful.

This little thought experiment suggests a few of the disadvantages of insider projects: the selection of the wrong kind of people, the excessive scope, the inability to take risks, the need to seem serious, the weight of expectations, the power of vested interests, the undiscerning audience, and perhaps most dangerous, the tendency of such work to become a duty rather than a pleasure.

Tests

A world with outsiders and insiders implies some kind of test for distinguishing between them. And the trouble with most tests for selecting elites is that there are two ways to pass them: to be good at what they try to measure, and to be good at hacking the test itself.

So the first question to ask about a field is how honest its tests are, because this tells you what it means to be an outsider. This tells you how much to trust your instincts when you disagree with authorities, whether it's worth going through the usual channels to become one yourself, and perhaps whether you want to work in this field at all.

Tests are least hackable when there are consistent standards for quality, and the people running the test really care about its integrity. Admissions to PhD programs in the hard sciences are fairly honest, for example. The professors will get whoever they admit as their own grad students, so they try hard to choose well, and they have a fair amount of data to go on. Whereas undergraduate admissions seem to be much more hackable.

One way to tell whether a field has consistent standards is the overlap between the leading practitioners and the people who teach the subject in universities. At one end of the scale you have fields like math and physics, where nearly all the teachers are among the best practitioners. In the middle are medicine, law, history, architecture, and computer science, where many are. At the bottom are business, literature, and the visual arts, where there's almost no overlap between the teachers and the leading practitioners. It's this end that gives rise to phrases like "those who can't do, teach."

Incidentally, this scale might be helpful in deciding what to study in college. When I was in college the rule seemed to be that you should study whatever you were most interested in. But in retrospect you're probably better off studying something moderately interesting with someone who's good at it than something very interesting with someone who isn't. You often hear people say that you shouldn't major in business in college, but this is actually an instance of a more general rule: don't learn things from teachers who are bad at them.

How much you should worry about being an outsider depends on the quality of the insiders. If you're an amateur mathematician and think you've solved a famous open problem, better go back and check. When I was in grad school, a friend in the math department had the job of replying to people who sent in proofs of Fermat's last theorem and so on, and it did not seem as if he saw it as a valuable source of tips—more like manning a mental health hotline. Whereas if the stuff you're writing seems different from what English professors are interested in, that's not necessarily a problem.

Anti-Tests

Where the method of selecting the elite is thoroughly corrupt, most of the good people will be outsiders. In art, for example, the image of the poor, misunderstood genius is not just one possible image of a great artist: it's the standard image. I'm not saying it's correct, incidentally, but it is telling how well this image has stuck. You couldn't make a rap like that stick to math or medicine. [2]

If it's corrupt enough, a test becomes an anti-test, filtering out the people it should select by making them to do things only the wrong people would do. Popularity in high school seems to be such a test. There are plenty of similar ones in the grownup world. For example, rising up through the hierarchy of the average big company demands an attention to politics few thoughtful people could spare. [3] Someone like Bill Gates can grow a company under him, but it's hard to imagine him having the patience to climb the corporate ladder at General Electric—or Microsoft, actually.

It's kind of strange when you think about it, because lord-of-the-flies schools and bureaucratic companies are both the default. There are probably a lot of people who go from one to the other and never realize the whole world doesn't work this way.

I think that's one reason big companies are so often blindsided by startups. People at big companies don't realize the extent to which they live in an environment that is one large, ongoing test for the wrong qualities.

If you're an outsider, your best chances for beating insiders are obviously in fields where corrupt tests select a lame elite. But there's a catch: if the tests are corrupt, your victory won't be recognized, at least in your lifetime. You may feel you don't need that, but history suggests it's dangerous to work in fields with corrupt tests. You may beat the insiders, and yet not do as good work, on an absolute scale, as you would in a field that was more honest.

Standards in art, for example, were almost as corrupt in the first half of the eighteenth century as they are today. This was the era of those fluffy idealized portraits of countesses with their lapdogs. Chardin decided to skip all that and paint ordinary things as he saw them. He's now considered the best of that period—and yet not the equal of Leonardo or Bellini or Memling, who all had the additional encouragement of honest standards.

It can be worth participating in a corrupt contest, however, if it's followed by another that isn't corrupt. For example, it would be worth competing with a company that can spend more than you on marketing, as long as you can survive to the next round, when customers compare your actual products. Similarly, you shouldn't be discouraged by the comparatively corrupt test of college admissions, because it's followed immediately by less hackable tests. [4]

Risk

Even in a field with honest tests, there are still advantages to being an outsider. The most obvious is that outsiders have nothing to lose. They can do risky things, and if they fail, so what? Few will even notice.

The eminent, on the other hand, are weighed down by their eminence. Eminence is like a suit: it impresses the wrong people, and it constrains the wearer.

Outsiders should realize the advantage they have here. Being able to take risks is hugely valuable. Everyone values safety too much, both the obscure and the eminent. No one wants to look like a fool. But it's very useful to be able to. If most of your ideas aren't stupid, you're probably being too conservative. You're not bracketing the problem.

Lord Acton said we should judge talent at its best and character at its worst. For example, if you write one great book and ten bad ones, you still count as a great writer—or at least, a better writer than someone who wrote eleven that were merely good. Whereas if you're a quiet, law-abiding citizen most of the time but occasionally cut someone up and bury them in your backyard, you're a bad guy.

Almost everyone makes the mistake of treating ideas as if they were indications of character rather than talent—as if having a stupid idea made you stupid. There's a huge weight of tradition advising us to play it safe. "Even a fool is thought wise if he keeps silent," says the Old Testament (Proverbs 17:28).

Well, that may be fine advice for a bunch of goatherds in Bronze Age Palestine. There conservatism would be the order of the day. But times have changed. It might still be reasonable to stick with the Old Testament in political questions, but materially the world now has a lot more state. Tradition is less of a guide, not just because things change faster, but because the space of possibilities is so large. The more complicated the world gets, the more valuable it is to be willing to look like a fool.

Delegation

And yet the more successful people become, the more heat they get if they screw up—or even seem to screw up. In this respect, as in many others, the eminent are prisoners of their own success. So the best way to understand the advantages of being an outsider may be to look at the disadvantages of being an insider.

If you ask eminent people what's wrong with their lives, the first thing they'll complain about is the lack of time. A friend of mine at Google is fairly high up in the company and went to work for them long before they went public. In other words, he's now rich enough not to have to work. I asked him if he could still endure the annoyances of having a job, now that he didn't have to. And he said that there weren't really any annoyances, except—and he got a wistful look when he said this—that he got so much email.

The eminent feel like everyone wants to take a bite out of them. The problem is so widespread that people pretending to be eminent do it by pretending to be overstretched.

The lives of the eminent become scheduled, and that's not good for thinking. One of the great advantages of being an outsider is long, uninterrupted blocks of time. That's what I remember about grad school: apparently endless supplies of time, which I spent worrying about, but not writing, my dissertation. Obscurity is like health food—unpleasant, perhaps, but good for you. Whereas fame tends to be like the alcohol produced by fermentation. When it reaches a certain concentration, it kills off the yeast that produced it.

The eminent generally respond to the shortage of time by turning into managers. They don't have time to work. They're surrounded by junior people they're supposed to help or supervise. The obvious solution is to have the junior people do the work. Some good stuff happens this way, but there are problems it doesn't work so well for: the kind where it helps to have everything in one head.

For example, it recently emerged that the famous glass artist Dale Chihuly hasn't actually blown glass for 27 years. He has assistants do the work for him. But one of the most valuable sources of ideas in the visual arts is the resistance of the medium. That's why oil paintings look so different from watercolors. In principle you could make any mark in any medium; in practice the medium steers you. And if you're no longer doing the work yourself, you stop learning from this.

So if you want to beat those eminent enough to delegate, one way to do it is to take advantage of direct contact with the medium. In the arts it's obvious how: blow your own glass, edit your own films, stage your own plays. And in the process pay close attention to accidents and to new ideas you have on the fly. This technique can be generalized to any sort of work: if you're an outsider, don't be ruled by plans. Planning is often just a weakness forced on those who delegate.

Is there a general rule for finding problems best solved in one head? Well, you can manufacture them by taking any project usually done by multiple people and trying to do it all yourself. Wozniak's work was a classic example: he did everything himself, hardware and software, and the result was miraculous. He claims not one bug was ever found in the Apple II, in either hardware or software.

Another way to find good problems to solve in one head is to focus on the grooves in the chocolate bar—the places where tasks are divided when they're split between several people. If you want to beat delegation, focus on a vertical slice: for example, be both writer and editor, or both design buildings and construct them.

One especially good groove to span is the one between tools and things made with them. For example, programming languages and applications are usually written by different people, and this is responsible for a lot of the worst flaws in programming languages. I think every language should be designed simultaneously with a large application written in it, the way C was with Unix.

Techniques for competing with delegation translate well into business, because delegation is endemic there. Instead of avoiding it as a drawback of senility, many companies embrace it as a sign of maturity. In big companies software is often designed, implemented, and sold by three separate types of people. In startups one person may have to do all three. And though this feels stressful, it's one reason startups win. The needs of customers and the means of satisfying them are all in one head.

Focus

The very skill of insiders can be a weakness. Once someone is good at something, they tend to spend all their time doing that. This kind of focus is very valuable, actually. Much of the skill of experts is the ability to ignore false trails. But focus has drawbacks: you don't learn from other fields, and when a new approach arrives, you may be the last to notice.

For outsiders this translates into two ways to win. One is to work on a variety of things. Since you can't derive as much benefit (yet) from a narrow focus, you may as well cast a wider net and derive what benefit you can from similarities between fields. Just as you can compete with delegation by working on larger vertical slices, you can compete with specialization by working on larger horizontal slices—by both writing and illustrating your book, for example.

The second way to compete with focus is to see what focus overlooks. In particular, new things. So if you're not good at anything yet, consider working on something so new that no one else is either. It won't have any prestige yet, if no one is good at it, but you'll have it all to yourself.

The potential of a new medium is usually underestimated, precisely because no one has yet explored its possibilities. Before Durer tried making engravings, no one took them very seriously. Engraving was for making little devotional images—basically fifteenth century baseball cards of saints. Trying to make masterpieces in this medium must have seemed to Durer's contemporaries that way that, say, making masterpieces in comics might seem to the average person today.

In the computer world we get not new mediums but new platforms: the minicomputer, the microprocessor, the web-based application. At first they're always dismissed as being unsuitable for real work. And yet someone always decides to try anyway, and it turns out you can do more than anyone expected. So in the future when you hear people say of a new platform: yeah, it's popular and cheap, but not ready yet for real work, jump on it.

As well as being more comfortable working on established lines, insiders generally have a vested interest in perpetuating them. The professor who made his reputation by discovering some new idea is not likely to be the one to discover its replacement. This is particularly true with companies, who have not only skill and pride anchoring them to the status quo, but money as well. The Achilles heel of successful companies is their inability to cannibalize themselves. Many innovations consist of replacing something with a cheaper alternative, and companies just don't want to see a path whose immediate effect is to cut an existing source of revenue.

So if you're an outsider you should actively seek out contrarian projects. Instead of working on things the eminent have made prestigious, work on things that could steal that prestige.

The really juicy new approaches are not the ones insiders reject as impossible, but those they ignore as undignified. For example, after Wozniak designed the Apple II he offered it first to his employer, HP. They passed. One of the reasons was that, to save money, he'd designed the Apple II to use a TV as a monitor, and HP felt they couldn't produce anything so declasse.

Less

Wozniak used a TV as a monitor for the simple reason that he couldn't afford a monitor. Outsiders are not merely free but compelled to make things that are cheap and lightweight. And both are good bets for growth: cheap things spread faster, and lightweight things evolve faster.

The eminent, on the other hand, are almost forced to work on a large scale. Instead of garden sheds they must design huge art museums. One reason they work on big things is that they can: like our hypothetical novelist, they're flattered by such opportunities. They also know that big projects will by their sheer bulk impress the audience. A garden shed, however lovely, would be easy to ignore; a few might even snicker at it. You can't snicker at a giant museum, no matter how much you dislike it. And finally, there are all those people the eminent have working for them; they have to choose projects that can keep them all busy.

Outsiders are free of all this. They can work on small things, and there's something very pleasing about small things. Small things can be perfect; big ones always have something wrong with them. But there's a magic in small things that goes beyond such rational explanations. All kids know it. Small things have more personality.

Plus making them is more fun. You can do what you want; you don't have to satisfy committees. And perhaps most important, small things can be done fast. The prospect of seeing the finished project hangs in the air like the smell of dinner cooking. If you work fast, maybe you could have it done tonight.

Working on small things is also a good way to learn. The most important kinds of learning happen one project at a time. ("Next time, I won't...") The faster you cycle through projects, the faster you'll evolve.

Plain materials have a charm like small scale. And in addition there's the challenge of making do with less. Every designer's ears perk up at the mention of that game, because it's a game you can't lose. Like the JV playing the varsity, if you even tie, you win. So paradoxically there are cases where fewer resources yield better results, because the designers' pleasure at their own ingenuity more than compensates. [5]

So if you're an outsider, take advantage of your ability to make small and inexpensive things. Cultivate the pleasure and simplicity of that kind of work; one day you'll miss it.

Responsibility

When you're old and eminent, what will you miss about being young and obscure? What people seem to miss most is the lack of responsibilities.

Responsibility is an occupational disease of eminence. In principle you could avoid it, just as in principle you could avoid getting fat as you get old, but few do. I sometimes suspect that responsibility is a trap and that the most virtuous route would be to shirk it, but regardless it's certainly constraining.

When you're an outsider you're constrained too, of course. You're short of money, for example. But that constrains you in different ways. How does responsibility constrain you? The worst thing is that it allows you not to focus on real work. Just as the most dangerous forms of procrastination are those that seem like work, the danger of responsibilities is not just that they can consume a whole day, but that they can do it without setting off the kind of alarms you'd set off if you spent a whole day sitting on a park bench.

A lot of the pain of being an outsider is being aware of one's own procrastination. But this is actually a good thing. You're at least close enough to work that the smell of it makes you hungry.

As an outsider, you're just one step away from getting things done. A huge step, admittedly, and one that most people never seem to make, but only one step. If you can summon up the energy to get started, you can work on projects with an intensity (in both senses) that few insiders can match. For insiders work turns into a duty, laden with responsibilities and expectations. It's never so pure as it was when they were young.

Work like a dog being taken for a walk, instead of an ox being yoked to the plow. That's what they miss.

Audience

A lot of outsiders make the mistake of doing the opposite; they admire the eminent so much that they copy even their flaws. Copying is a good way to learn, but copy the right things. When I was in college I imitated the pompous diction of famous professors. But this wasn't what made them eminent—it was more a flaw their eminence had allowed them to sink into. Imitating it was like pretending to have gout in order to seem rich.

Half the distinguishing qualities of the eminent are actually disadvantages. Imitating these is not only a waste of time, but will make you seem a fool to your models, who are often well aware of it.

What are the genuine advantages of being an insider? The greatest is an audience. It often seems to outsiders that the great advantage of insiders is money—that they have the resources to do what they want. But so do people who inherit money, and that doesn't seem to help, not as much as an audience. It's good for morale to know people want to see what you're making; it draws work out of you.

If I'm right that the defining advantage of insiders is an audience, then we live in exciting times, because just in the last ten years the Internet has made audiences a lot more liquid. Outsiders don't have to content themselves anymore with a proxy audience of a few smart friends. Now, thanks to the Internet, they can start to grow themselves actual audiences. This is great news for the marginal, who retain the advantages of outsiders while increasingly being able to siphon off what had till recently been the prerogative of the elite.

Though the Web has been around for more than ten years, I think we're just beginning to see its democratizing effects. Outsiders are still learning how to steal audiences. But more importantly, audiences are still learning how to be stolen—they're still just beginning to realize how much deeper bloggers can dig than journalists, how much more interesting a democratic news site can be than a front page controlled by editors, and how much funnier a bunch of kids with webcams can be than mass-produced sitcoms.

The big media companies shouldn't worry that people will post their copyrighted material on YouTube. They should worry that people will post their own stuff on YouTube, and audiences will watch that instead.

Hacking

If I had to condense the power of the marginal into one sentence it would be: just try hacking something together. That phrase draws in most threads I've mentioned here. Hacking something together means deciding what to do as you're doing it, not a subordinate executing the vision of his boss. It implies the result won't be pretty, because it will be made quickly out of inadequate materials. It may work, but it won't be the sort of thing the eminent would want to put their name on. Something hacked together means something that barely solves the problem, or maybe doesn't solve the problem at all, but another you discovered en route. But that's ok, because the main value of that initial version is not the thing itself, but what it leads to. Insiders who daren't walk through the mud in their nice clothes will never make it to the solid ground on the other side.

The word "try" is an especially valuable component. I disagree here with Yoda, who said there is no try. There is try. It implies there's no punishment if you fail. You're driven by curiosity instead of duty. That means the wind of procrastination will be in your favor: instead of avoiding this work, this will be what you do as a way of avoiding other work. And when you do it, you'll be in a better mood. The more the work depends on imagination, the more that matters, because most people have more ideas when they're happy.

If I could go back and redo my twenties, that would be one thing I'd do more of: just try hacking things together. Like many people that age, I spent a lot of time worrying about what I should do. I also spent some time trying to build stuff. I should have spent less time worrying and more time building. If you're not sure what to do, make something.

Raymond Chandler's advice to thriller writers was "When in doubt, have a man come through a door with a gun in his hand." He followed that advice. Judging from his books, he was often in doubt. But though the result is occasionally cheesy, it's never boring. In life, as in books, action is underrated.

Fortunately the number of things you can just hack together keeps increasing. People fifty years ago would be astonished that one could just hack together a movie, for example. Now you can even hack together distribution. Just make stuff and put it online.

Inappropriate

If you really want to score big, the place to focus is the margin of the margin: the territories only recently captured from the insiders. That's where you'll find the juiciest projects still undone, either because they seemed too risky, or simply because there were too few insiders to explore everything.

This is why I spend most of my time writing essays lately. The writing of essays used to be limited to those who could get them published. In principle you could have written them and just shown them to your friends; in practice that didn't work. [6] An essayist needs the resistance of an audience, just as an engraver needs the resistance of the plate.

Up till a few years ago, writing essays was the ultimate insider's game. Domain experts were allowed to publish essays about their field, but the pool allowed to write on general topics was about eight people who went to the right parties in New York. Now the reconquista has overrun this territory, and, not surprisingly, found it sparsely cultivated. There are so many essays yet unwritten. They tend to be the naughtier ones; the insiders have pretty much exhausted the motherhood and apple pie topics.

This leads to my final suggestion: a technique for determining when you're on the right track. You're on the right track when people complain that you're unqualified, or that you've done something inappropriate. If people are complaining, that means you're doing something rather than sitting around, which is the first step. And if they're driven to such empty forms of complaint, that means you've probably done something good.

If you make something and people complain that it doesn't work, that's a problem. But if the worst thing they can hit you with is your own status as an outsider, that implies that in every other respect you've succeeded. Pointing out that someone is unqualified is as desperate as resorting to racial slurs. It's just a legitimate sounding way of saying: we don't like your type around here.

But the best thing of all is when people call what you're doing inappropriate. I've been hearing this word all my life and I only recently realized that it is, in fact, the sound of the homing beacon. "Inappropriate" is the null criticism. It's merely the adjective form of "I don't like it."

So that, I think, should be the highest goal for the marginal. Be inappropriate. When you hear people saying that, you're golden. And they, incidentally, are busted.





Notes

[1] The facts about Apple's early history are from an interview with Steve Wozniak in Jessica Livingston's Founders at Work.

[2] As usual the popular image is several decades behind reality. Now the misunderstood artist is not a chain-smoking drunk who pours his soul into big, messy canvases that philistines see and say "that's not art" because it isn't a picture of anything. The philistines have now been trained that anything hung on a wall is art. Now the misunderstood artist is a coffee-drinking vegan cartoonist whose work they see and say "that's not art" because it looks like stuff they've seen in the Sunday paper.

[3] In fact this would do fairly well as a definition of politics: what determines rank in the absence of objective tests.

[4] In high school you're led to believe your whole future depends on where you go to college, but it turns out only to buy you a couple years. By your mid-twenties the people worth impressing already judge you more by what you've done than where you went to school.

[5] Managers are presumably wondering, how can I make this miracle happen? How can I make the people working for me do more with less? Unfortunately the constraint probably has to be self-imposed. If you're expected to do more with less, then you're being starved, not eating virtuously.

[6] Without the prospect of publication, the closest most people come to writing essays is to write in a journal. I find I never get as deeply into subjects as I do in proper essays. As the name implies, you don't go back and rewrite journal entries over and over for two weeks.

Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Sarah Harlin, Jessica Livingston, Jackie McDonough, Robert Morris, Olin Shivers, and Chris Small for reading drafts of this, and to Chris Small and Chad Fowler for inviting me to speak.

Want to start a startup? Get funded by Y Combinator.

November 2012

The way to get startup ideas is not to try to think of startup ideas. It's to look for problems, preferably problems you have yourself.

The very best startup ideas tend to have three things in common: they're something the founders themselves want, that they themselves can build, and that few others realize are worth doing. Microsoft, Apple, Yahoo, Google, and Facebook all began this way.

Problems

Why is it so important to work on a problem you have? Among other things, it ensures the problem really exists. It sounds obvious to say you should only work on problems that exist. And yet by far the most common mistake startups make is to solve problems no one has.

I made it myself. In 1995 I started a company to put art galleries online. But galleries didn't want to be online. It's not how the art business works. So why did I spend 6 months working on this stupid idea? Because I didn't pay attention to users. I invented a model of the world that didn't correspond to reality, and worked from that. I didn't notice my model was wrong until I tried to convince users to pay for what we'd built. Even then I took embarrassingly long to catch on. I was attached to my model of the world, and I'd spent a lot of time on the software. They had to want it!

Why do so many founders build things no one wants? Because they begin by trying to think of startup ideas. That m.o. is doubly dangerous: it doesn't merely yield few good ideas; it yields bad ideas that sound plausible enough to fool you into working on them.

At YC we call these "made-up" or "sitcom" startup ideas. Imagine one of the characters on a TV show was starting a startup. The writers would have to invent something for it to do. But coming up with good startup ideas is hard. It's not something you can do for the asking. So (unless they got amazingly lucky) the writers would come up with an idea that sounded plausible, but was actually bad.

For example, a social network for pet owners. It doesn't sound obviously mistaken. Millions of people have pets. Often they care a lot about their pets and spend a lot of money on them. Surely many of these people would like a site where they could talk to other pet owners. Not all of them perhaps, but if just 2 or 3 percent were regular visitors, you could have millions of users. You could serve them targeted offers, and maybe charge for premium features. [1]

The danger of an idea like this is that when you run it by your friends with pets, they don't say "I would never use this." They say "Yeah, maybe I could see using something like that." Even when the startup launches, it will sound plausible to a lot of people. They don't want to use it themselves, at least not right now, but they could imagine other people wanting it. Sum that reaction across the entire population, and you have zero users. [2]

Well

When a startup launches, there have to be at least some users who really need what they're making—not just people who could see themselves using it one day, but who want it urgently. Usually this initial group of users is small, for the simple reason that if there were something that large numbers of people urgently needed and that could be built with the amount of effort a startup usually puts into a version one, it would probably already exist. Which means you have to compromise on one dimension: you can either build something a large number of people want a small amount, or something a small number of people want a large amount. Choose the latter. Not all ideas of that type are good startup ideas, but nearly all good startup ideas are of that type.

Imagine a graph whose x axis represents all the people who might want what you're making and whose y axis represents how much they want it. If you invert the scale on the y axis, you can envision companies as holes. Google is an immense crater: hundreds of millions of people use it, and they need it a lot. A startup just starting out can't expect to excavate that much volume. So you have two choices about the shape of hole you start with. You can either dig a hole that's broad but shallow, or one that's narrow and deep, like a well.

Made-up startup ideas are usually of the first type. Lots of people are mildly interested in a social network for pet owners.

Nearly all good startup ideas are of the second type. Microsoft was a well when they made Altair Basic. There were only a couple thousand Altair owners, but without this software they were programming in machine language. Thirty years later Facebook had the same shape. Their first site was exclusively for Harvard students, of which there are only a few thousand, but those few thousand users wanted it a lot.

When you have an idea for a startup, ask yourself: who wants this right now? Who wants this so much that they'll use it even when it's a crappy version one made by a two-person startup they've never heard of? If you can't answer that, the idea is probably bad. [3]

You don't need the narrowness of the well per se. It's depth you need; you get narrowness as a byproduct of optimizing for depth (and speed). But you almost always do get it. In practice the link between depth and narrowness is so strong that it's a good sign when you know that an idea will appeal strongly to a specific group or type of user.

But while demand shaped like a well is almost a necessary condition for a good startup idea, it's not a sufficient one. If Mark Zuckerberg had built something that could only ever have appealed to Harvard students, it would not have been a good startup idea. Facebook was a good idea because it started with a small market there was a fast path out of. Colleges are similar enough that if you build a facebook that works at Harvard, it will work at any college. So you spread rapidly through all the colleges. Once you have all the college students, you get everyone else simply by letting them in.

Similarly for Microsoft: Basic for the Altair; Basic for other machines; other languages besides Basic; operating systems; applications; IPO.

Self

How do you tell whether there's a path out of an idea? How do you tell whether something is the germ of a giant company, or just a niche product? Often you can't. The founders of Airbnb didn't realize at first how big a market they were tapping. Initially they had a much narrower idea. They were going to let hosts rent out space on their floors during conventions. They didn't foresee the expansion of this idea; it forced itself upon them gradually. All they knew at first is that they were onto something. That's probably as much as Bill Gates or Mark Zuckerberg knew at first.

Occasionally it's obvious from the beginning when there's a path out of the initial niche. And sometimes I can see a path that's not immediately obvious; that's one of our specialties at YC. But there are limits to how well this can be done, no matter how much experience you have. The most important thing to understand about paths out of the initial idea is the meta-fact that these are hard to see.

So if you can't predict whether there's a path out of an idea, how do you choose between ideas? The truth is disappointing but interesting: if you're the right sort of person, you have the right sort of hunches. If you're at the leading edge of a field that's changing fast, when you have a hunch that something is worth doing, you're more likely to be right.

In Zen and the Art of Motorcycle Maintenance, Robert Pirsig says:

You want to know how to paint a perfect painting? It's easy. Make yourself perfect and then just paint naturally.

Live in the future, then build what's missing.

Live in the future and build what seems interesting.

(These are some notes I made for a panel discussion on programming language design at MIT on May 10, 2001.)





1. Programming Languages Are for People.

Programming languages are how people talk to computers. The computer would be just as happy speaking any language that was unambiguous. The reason we have high level languages is because people can't deal with machine language. The point of programming languages is to prevent our poor frail human brains from being overwhelmed by a mass of detail.

Architects know that some kinds of design problems are more personal than others. One of the cleanest, most abstract design problems is designing bridges. There your job is largely a matter of spanning a given distance with the least material. The other end of the spectrum is designing chairs. Chair designers have to spend their time thinking about human butts.

Software varies in the same way. Designing algorithms for routing data through a network is a nice, abstract problem, like designing bridges. Whereas designing programming languages is like designing chairs: it's all about dealing with human weaknesses.

Most of us hate to acknowledge this. Designing systems of great mathematical elegance sounds a lot more appealing to most of us than pandering to human weaknesses. And there is a role for mathematical elegance: some kinds of elegance make programs easier to understand. But elegance is not an end in itself.

And when I say languages have to be designed to suit human weaknesses, I don't mean that languages have to be designed for bad programmers. In fact I think you ought to design for the best programmers, but even the best programmers have limitations. I don't think anyone would like programming in a language where all the variables were the letter x with integer subscripts.

2. Design for Yourself and Your Friends.

If you look at the history of programming languages, a lot of the best ones were languages designed for their own authors to use, and a lot of the worst ones were designed for other people to use.

When languages are designed for other people, it's always a specific group of other people: people not as smart as the language designer. So you get a language that talks down to you. Cobol is the most extreme case, but a lot of languages are pervaded by this spirit.

It has nothing to do with how abstract the language is. C is pretty low-level, but it was designed for its authors to use, and that's why hackers like it.

The argument for designing languages for bad programmers is that there are more bad programmers than good programmers. That may be so. But those few good programmers write a disproportionately large percentage of the software.

I'm interested in the question, how do you design a language that the very best hackers will like? I happen to think this is identical to the question, how do you design a good programming language?, but even if it isn't, it is at least an interesting question.

3. Give the Programmer as Much Control as Possible.

Many languages (especially the ones designed for other people) have the attitude of a governess: they try to prevent you from doing things that they think aren't good for you. I like the opposite approach: give the programmer as much control as you can.

When I first learned Lisp, what I liked most about it was that it considered me an equal partner. In the other languages I had learned up till then, there was the language and there was my program, written in the language, and the two were very separate. But in Lisp the functions and macros I wrote were just like those that made up the language itself. I could rewrite the language if I wanted. It had the same appeal as open-source software.

4. Aim for Brevity.

Brevity is underestimated and even scorned. But if you look into the hearts of hackers, you'll see that they really love it. How many times have you heard hackers speak fondly of how in, say, APL, they could do amazing things with just a couple lines of code? I think anything that really smart people really love is worth paying attention to.

I think almost anything you can do to make programs shorter is good. There should be lots of library functions; anything that can be implicit should be; the syntax should be terse to a fault; even the names of things should be short.

And it's not only programs that should be short. The manual should be thin as well. A good part of manuals is taken up with clarifications and reservations and warnings and special cases. If you force yourself to shorten the manual, in the best case you do it by fixing the things in the language that required so much explanation.

5. Admit What Hacking Is.

A lot of people wish that hacking was mathematics, or at least something like a natural science. I think hacking is more like architecture. Architecture is related to physics, in the sense that architects have to design buildings that don't fall down, but the actual goal of architects is to make great buildings, not to make discoveries about statics.

What hackers like to do is make great programs. And I think, at least in our own minds, we have to remember that it's an admirable thing to write great programs, even when this work doesn't translate easily into the conventional intellectual currency of research papers. Intellectually, it is just as worthwhile to design a language programmers will love as it is to design a horrible one that embodies some idea you can publish a paper about.





1. How to Organize Big Libraries?

Libraries are becoming an increasingly important component of programming languages. They're also getting bigger, and this can be dangerous. If it takes longer to find the library function that will do what you want than it would take to write it yourself, then all that code is doing nothing but make your manual thick. (The Symbolics manuals were a case in point.) So I think we will have to work on ways to organize libraries. The ideal would be to design them so that the programmer could guess what library call would do the right thing.

2. Are People Really Scared of Prefix Syntax?

This is an open problem in the sense that I have wondered about it for years and still don't know the answer. Prefix syntax seems perfectly natural to me, except possibly for math. But it could be that a lot of Lisp's unpopularity is simply due to having an unfamiliar syntax. Whether to do anything about it, if it is true, is another question.

3. What Do You Need for Server-Based Software?

I think a lot of the most exciting new applications that get written in the next twenty years will be Web-based applications, meaning programs that sit on the server and talk to you through a Web browser. And to write these kinds of programs we may need some new things.

One thing we'll need is support for the new way that server-based apps get released. Instead of having one or two big releases a year, like desktop software, server-based apps get released as a series of small changes. You may have as many as five or ten releases a day. And as a rule everyone will always use the latest version.

You know how you can design programs to be debuggable? Well, server-based software likewise has to be designed to be changeable. You have to be able to change it easily, or at least to know what is a small change and what is a momentous one.

Another thing that might turn out to be useful for server based software, surprisingly, is continuations. In Web-based software you can use something like continuation-passing style to get the effect of subroutines in the inherently stateless world of a Web session. Maybe it would be worthwhile having actual continuations, if it was not too expensive.

4. What New Abstractions Are Left to Discover?

I'm not sure how reasonable a hope this is, but one thing I would really love to do, personally, is discover a new abstraction-- something that would make as much of a difference as having first class functions or recursion or even keyword parameters. This may be an impossible dream. These things don't get discovered that often. But I am always looking.





1. You Can Use Whatever Language You Want.

Writing application programs used to mean writing desktop software. And in desktop software there is a big bias toward writing the application in the same language as the operating system. And so ten years ago, writing software pretty much meant writing software in C. Eventually a tradition evolved: application programs must not be written in unusual languages. And this tradition had so long to develop that nontechnical people like managers and venture capitalists also learned it.

Server-based software blows away this whole model. With server-based software you can use any language you want. Almost nobody understands this yet (especially not managers and venture capitalists). A few hackers understand it, and that's why we even hear about new, indy languages like Perl and Python. We're not hearing about Perl and Python because people are using them to write Windows apps.

What this means for us, as people interested in designing programming languages, is that there is now potentially an actual audience for our work.

2. Speed Comes from Profilers.

Language designers, or at least language implementors, like to write compilers that generate fast code. But I don't think this is what makes languages fast for users. Knuth pointed out long ago that speed only matters in a few critical bottlenecks. And anyone who's tried it knows that you can't guess where these bottlenecks are. Profilers are the answer.

Language designers are solving the wrong problem. Users don't need benchmarks to run fast. What they need is a language that can show them what parts of their own programs need to be rewritten. That's where speed comes from in practice. So maybe it would be a net win if language implementors took half the time they would have spent doing compiler optimizations and spent it writing a good profiler instead.

3. You Need an Application to Drive the Design of a Language.

This may not be an absolute rule, but it seems like the best languages all evolved together with some application they were being used to write. C was written by people who needed it for systems programming. Lisp was developed partly to do symbolic differentiation, and McCarthy was so eager to get started that he was writing differentiation programs even in the first paper on Lisp, in 1960.

It's especially good if your application solves some new problem. That will tend to drive your language to have new features that programmers need. I personally am interested in writing a language that will be good for writing server-based applications.

[During the panel, Guy Steele also made this point, with the additional suggestion that the application should not consist of writing the compiler for your language, unless your language happens to be intended for writing compilers.]

4. A Language Has to Be Good for Writing Throwaway Programs.

You know what a throwaway program is: something you write quickly for some limited task. I think if you looked around you'd find that a lot of big, serious programs started as throwaway programs. I would not be surprised if most programs started as throwaway programs. And so if you want to make a language that's good for writing software in general, it has to be good for writing throwaway programs, because that is the larval stage of most software.

5. Syntax Is Connected to Semantics.

It's traditional to think of syntax and semantics as being completely separate. This will sound shocking, but it may be that they aren't. I think that what you want in your language may be related to how you express it.

I was talking recently to Robert Morris, and he pointed out that operator overloading is a bigger win in languages with infix syntax. In a language with prefix syntax, any function you define is effectively an operator. If you want to define a plus for a new type of number you've made up, you can just define a new function to add them. If you do that in a language with infix syntax, there's a big difference in appearance between the use of an overloaded operator and a function call.





1. New Programming Languages.

Back in the 1970s it was fashionable to design new programming languages. Recently it hasn't been. But I think server-based software will make new languages fashionable again. With server-based software, you can use any language you want, so if someone does design a language that actually seems better than others that are available, there will be people who take a risk and use it.

2. Time-Sharing.

Richard Kelsey gave this as an idea whose time has come again in the last panel, and I completely agree with him. My guess (and Microsoft's guess, it seems) is that much computing will move from the desktop onto remote servers. In other words, time-sharing is back. And I think there will need to be support for it at the language level. For example, I know that Richard and Jonathan Rees have done a lot of work implementing process scheduling within Scheme 48.

3. Efficiency.

Recently it was starting to seem that computers were finally fast enough. More and more we were starting to hear about byte code, which implies to me at least that we feel we have cycles to spare. But I don't think we will, with server-based software. Someone is going to have to pay for the servers that the software runs on, and the number of users they can support per machine will be the divisor of their capital cost.

So I think efficiency will matter, at least in computational bottlenecks. It will be especially important to do i/o fast, because server-based applications do a lot of i/o.

It may turn out that byte code is not a win, in the end. Sun and Microsoft seem to be facing off in a kind of a battle of the byte codes at the moment. But they're doing it because byte code is a convenient place to insert themselves into the process, not because byte code is in itself a good idea. It may turn out that this whole battleground gets bypassed. That would be kind of amusing.





1. Clients.

This is just a guess, but my guess is that the winning model for most applications will be purely server-based. Designing software that works on the assumption that everyone will have your client is like designing a society on the assumption that everyone will just be honest. It would certainly be convenient, but you have to assume it will never happen.

I think there will be a proliferation of devices that have some kind of Web access, and all you'll be able to assume about them is that they can support simple html and forms. Will you have a browser on your cell phone? Will there be a phone in your palm pilot? Will your blackberry get a bigger screen? Will you be able to browse the Web on your gameboy? Your watch? I don't know. And I don't have to know if I bet on everything just being on the server. It's just so much more robust to have all the brains on the server.

2. Object-Oriented Programming.

I realize this is a controversial one, but I don't think object-oriented programming is such a big deal. I think it is a fine model for certain kinds of applications that need that specific kind of data structure, like window systems, simulations, and cad programs. But I don't see why it ought to be the model for all programming.

I think part of the reason people in big companies like object-oriented programming is because it yields a lot of what looks like work. Something that might naturally be represented as, say, a list of integers, can now be represented as a class with all kinds of scaffolding and hustle and bustle.

Another attraction of object-oriented programming is that methods give you some of the effect of first class functions. But this is old news to Lisp programmers. When you have actual first class functions, you can just use them in whatever way is appropriate to the task at hand, instead of forcing everything into a mold of classes and methods.

What this means for language design, I think, is that you shouldn't build object-oriented programming in too deeply. Maybe the answer is to offer more general, underlying stuff, and let people design whatever object systems they want as libraries.

3. Design by Committee.

Having your language designed by a committee is a big pitfall, and not just for the reasons everyone knows about. Everyone knows that committees tend to yield lumpy, inconsistent designs. But I think a greater danger is that they won't take risks. When one person is in charge he can take risks that a committee would never agree on.

Is it necessary to take risks to design a good language though? Many people might suspect that language design is something where you should stick fairly close to the conventional wisdom. I bet this isn't true. In everything else people do, reward is proportionate to risk. Why should language design be any different?

Want to start a startup? Get funded by Y Combinator.

January 2006

To do something well you have to like it. That idea is not exactly novel. We've got it down to four words: "Do what you love." But it's not enough just to tell people that. Doing what you love is complicated.

The very idea is foreign to what most of us learn as kids. When I was a kid, it seemed as if work and fun were opposites by definition. Life had two states: some of the time adults were making you do things, and that was called work; the rest of the time you could do what you wanted, and that was called playing. Occasionally the things adults made you do were fun, just as, occasionally, playing wasn't—for example, if you fell and hurt yourself. But except for these few anomalous cases, work was pretty much defined as not-fun.

And it did not seem to be an accident. School, it was implied, was tedious because it was preparation for grownup work.

The world then was divided into two groups, grownups and kids. Grownups, like some kind of cursed race, had to work. Kids didn't, but they did have to go to school, which was a dilute version of work meant to prepare us for the real thing. Much as we disliked school, the grownups all agreed that grownup work was worse, and that we had it easy.

Teachers in particular all seemed to believe implicitly that work was not fun. Which is not surprising: work wasn't fun for most of them. Why did we have to memorize state capitals instead of playing dodgeball? For the same reason they had to watch over a bunch of kids instead of lying on a beach. You couldn't just do what you wanted.

I'm not saying we should let little kids do whatever they want. They may have to be made to work on certain things. But if we make kids work on dull stuff, it might be wise to tell them that tediousness is not the defining quality of work, and indeed that the reason they have to work on dull stuff now is so they can work on more interesting stuff later. [1]

Once, when I was about 9 or 10, my father told me I could be whatever I wanted when I grew up, so long as I enjoyed it. I remember that precisely because it seemed so anomalous. It was like being told to use dry water. Whatever I thought he meant, I didn't think he meant work could literally be fun—fun like playing. It took me years to grasp that.

Jobs

By high school, the prospect of an actual job was on the horizon. Adults would sometimes come to speak to us about their work, or we would go to see them at work. It was always understood that they enjoyed what they did. In retrospect I think one may have: the private jet pilot. But I don't think the bank manager really did.

The main reason they all acted as if they enjoyed their work was presumably the upper-middle class convention that you're supposed to. It would not merely be bad for your career to say that you despised your job, but a social faux-pas.

Why is it conventional to pretend to like what you do? The first sentence of this essay explains that. If you have to like something to do it well, then the most successful people will all like what they do. That's where the upper-middle class tradition comes from. Just as houses all over America are full of chairs that are, without the owners even knowing it, nth-degree imitations of chairs designed 250 years ago for French kings, conventional attitudes about work are, without the owners even knowing it, nth-degree imitations of the attitudes of people who've done great things.

What a recipe for alienation. By the time they reach an age to think about what they'd like to do, most kids have been thoroughly misled about the idea of loving one's work. School has trained them to regard work as an unpleasant duty. Having a job is said to be even more onerous than schoolwork. And yet all the adults claim to like what they do. You can't blame kids for thinking "I am not like these people; I am not suited to this world."

Actually they've been told three lies: the stuff they've been taught to regard as work in school is not real work; grownup work is not (necessarily) worse than schoolwork; and many of the adults around them are lying when they say they like what they do.

The most dangerous liars can be the kids' own parents. If you take a boring job to give your family a high standard of living, as so many people do, you risk infecting your kids with the idea that work is boring. [2] Maybe it would be better for kids in this one case if parents were not so unselfish. A parent who set an example of loving their work might help their kids more than an expensive house. [3]

It was not till I was in college that the idea of work finally broke free from the idea of making a living. Then the important question became not how to make money, but what to work on. Ideally these coincided, but some spectacular boundary cases (like Einstein in the patent office) proved they weren't identical.

The definition of work was now to make some original contribution to the world, and in the process not to starve. But after the habit of so many years my idea of work still included a large component of pain. Work still seemed to require discipline, because only hard problems yielded grand results, and hard problems couldn't literally be fun. Surely one had to force oneself to work on them.

If you think something's supposed to hurt, you're less likely to notice if you're doing it wrong. That about sums up my experience of graduate school.

Bounds

How much are you supposed to like what you do? Unless you know that, you don't know when to stop searching. And if, like most people, you underestimate it, you'll tend to stop searching too early. You'll end up doing something chosen for you by your parents, or the desire to make money, or prestige—or sheer inertia.

Here's an upper bound: Do what you love doesn't mean, do what you would like to do most this second. Even Einstein probably had moments when he wanted to have a cup of coffee, but told himself he ought to finish what he was working on first.

It used to perplex me when I read about people who liked what they did so much that there was nothing they'd rather do. There didn't seem to be any sort of work I liked that much. If I had a choice of (a) spending the next hour working on something or (b) be teleported to Rome and spend the next hour wandering about, was there any sort of work I'd prefer? Honestly, no.

But the fact is, almost anyone would rather, at any given moment, float about in the Carribbean, or have sex, or eat some delicious food, than work on hard problems. The rule about doing what you love assumes a certain length of time. It doesn't mean, do what will make you happiest this second, but what will make you happiest over some longer period, like a week or a month.

Unproductive pleasures pall eventually. After a while you get tired of lying on the beach. If you want to stay happy, you have to do something.

As a lower bound, you have to like your work more than any unproductive pleasure. You have to like what you do enough that the concept of "spare time" seems mistaken. Which is not to say you have to spend all your time working. You can only work so much before you get tired and start to screw up. Then you want to do something else—even something mindless. But you don't regard this time as the prize and the time you spend working as the pain you endure to earn it.

I put the lower bound there for practical reasons. If your work is not your favorite thing to do, you'll have terrible problems with procrastination. You'll have to force yourself to work, and when you resort to that the results are distinctly inferior.

To be happy I think you have to be doing something you not only enjoy, but admire. You have to be able to say, at the end, wow, that's pretty cool. This doesn't mean you have to make something. If you learn how to hang glide, or to speak a foreign language fluently, that will be enough to make you say, for a while at least, wow, that's pretty cool. What there has to be is a test.

So one thing that falls just short of the standard, I think, is reading books. Except for some books in math and the hard sciences, there's no test of how well you've read a book, and that's why merely reading books doesn't quite feel like work. You have to do something with what you've read to feel productive.

I think the best test is one Gino Lee taught me: to try to do things that would make your friends say wow. But it probably wouldn't start to work properly till about age 22, because most people haven't had a big enough sample to pick friends from before then.

Sirens

What you should not do, I think, is worry about the opinion of anyone beyond your friends. You shouldn't worry about prestige. Prestige is the opinion of the rest of the world. When you can ask the opinions of people whose judgement you respect, what does it add to consider the opinions of people you don't even know? [4]

This is easy advice to give. It's hard to follow, especially when you're young. [5] Prestige is like a powerful magnet that warps even your beliefs about what you enjoy. It causes you to work not on what you like, but what you'd like to like.

That's what leads people to try to write novels, for example. They like reading novels. They notice that people who write them win Nobel prizes. What could be more wonderful, they think, than to be a novelist? But liking the idea of being a novelist is not enough; you have to like the actual work of novel-writing if you're going to be good at it; you have to like making up elaborate lies.

Prestige is just fossilized inspiration. If you do anything well enough, you'll make it prestigious. Plenty of things we now consider prestigious were anything but at first. Jazz comes to mind—though almost any established art form would do. So just do what you like, and let prestige take care of itself.

Prestige is especially dangerous to the ambitious. If you want to make ambitious people waste their time on errands, the way to do it is to bait the hook with prestige. That's the recipe for getting people to give talks, write forewords, serve on committees, be department heads, and so on. It might be a good rule simply to avoid any prestigious task. If it didn't suck, they wouldn't have had to make it prestigious.

Similarly, if you admire two kinds of work equally, but one is more prestigious, you should probably choose the other. Your opinions about what's admirable are always going to be slightly influenced by prestige, so if the two seem equal to you, you probably have more genuine admiration for the less prestigious one.

The other big force leading people astray is money. Money by itself is not that dangerous. When something pays well but is regarded with contempt, like telemarketing, or prostitution, or personal injury litigation, ambitious people aren't tempted by it. That kind of work ends up being done by people who are "just trying to make a living." (Tip: avoid any field whose practitioners say this.) The danger is when money is combined with prestige, as in, say, corporate law, or medicine. A comparatively safe and prosperous career with some automatic baseline prestige is dangerously tempting to someone young, who hasn't thought much about what they really like.

The test of whether people love what they do is whether they'd do it even if they weren't paid for it—even if they had to work at another job to make a living. How many corporate lawyers would do their current work if they had to do it for free, in their spare time, and take day jobs as waiters to support themselves?

This test is especially helpful in deciding between different kinds of academic work, because fields vary greatly in this respect. Most good mathematicians would work on math even if there were no jobs as math professors, whereas in the departments at the other end of the spectrum, the availability of teaching jobs is the driver: people would rather be English professors than work in ad agencies, and publishing papers is the way you compete for such jobs. Math would happen without math departments, but it is the existence of English majors, and therefore jobs teaching them, that calls into being all those thousands of dreary papers about gender and identity in the novels of Conrad. No one does that kind of thing for fun.

The advice of parents will tend to err on the side of money. It seems safe to say there are more undergrads who want to be novelists and whose parents want them to be doctors than who want to be doctors and whose parents want them to be novelists. The kids think their parents are "materialistic." Not necessarily. All parents tend to be more conservative for their kids than they would for themselves, simply because, as parents, they share risks more than rewards. If your eight year old son decides to climb a tall tree, or your teenage daughter decides to date the local bad boy, you won't get a share in the excitement, but if your son falls, or your daughter gets pregnant, you'll have to deal with the consequences.

Discipline

With such powerful forces leading us astray, it's not surprising we find it so hard to discover what we like to work on. Most people are doomed in childhood by accepting the axiom that work = pain. Those who escape this are nearly all lured onto the rocks by prestige or money. How many even discover something they love to work on? A few hundred thousand, perhaps, out of billions.

It's hard to find work you love; it must be, if so few do. So don't underestimate this task. And don't feel bad if you haven't succeeded yet. In fact, if you admit to yourself that you're discontented, you're a step ahead of most people, who are still in denial. If you're surrounded by colleagues who claim to enjoy work that you find contemptible, odds are they're lying to themselves. Not necessarily, but probably.

Although doing great work takes less discipline than people think—because the way to do great work is to find something you like so much that you don't have to force yourself to do it—finding work you love does usually require discipline. Some people are lucky enough to know what they want to do when they're 12, and just glide along as if they were on railroad tracks. But this seems the exception. More often people who do great things have careers with the trajectory of a ping-pong ball. They go to school to study A, drop out and get a job doing B, and then become famous for C after taking it up on the side.

Sometimes jumping from one sort of work to another is a sign of energy, and sometimes it's a sign of laziness. Are you dropping out, or boldly carving a new path? You often can't tell yourself. Plenty of people who will later do great things seem to be disappointments early on, when they're trying to find their niche.

Is there some test you can use to keep yourself honest? One is to try to do a good job at whatever you're doing, even if you don't like it. Then at least you'll know you're not using dissatisfaction as an excuse for being lazy. Perhaps more importantly, you'll get into the habit of doing things well.

Another test you can use is: always produce. For example, if you have a day job you don't take seriously because you plan to be a novelist, are you producing? Are you writing pages of fiction, however bad? As long as you're producing, you'll know you're not merely using the hazy vision of the grand novel you plan to write one day as an opiate. The view of it will be obstructed by the all too palpably flawed one you're actually writing.

"Always produce" is also a heuristic for finding the work you love. If you subject yourself to that constraint, it will automatically push you away from things you think you're supposed to work on, toward things you actually like. "Always produce" will discover your life's work the way water, with the aid of gravity, finds the hole in your roof.

Of course, figuring out what you like to work on doesn't mean you get to work on it. That's a separate question. And if you're ambitious you have to keep them separate: you have to make a conscious effort to keep your ideas about what you want from being contaminated by what seems possible. [6]

It's painful to keep them apart, because it's painful to observe the gap between them. So most people pre-emptively lower their expectations. For example, if you asked random people on the street if they'd like to be able to draw like Leonardo, you'd find most would say something like "Oh, I can't draw." This is more a statement of intention than fact; it means, I'm not going to try. Because the fact is, if you took a random person off the street and somehow got them to work as hard as they possibly could at drawing for the next twenty years, they'd get surprisingly far. But it would require a great moral effort; it would mean staring failure in the eye every day for years. And so to protect themselves people say "I can't."

Another related line you often hear is that not everyone can do work they love—that someone has to do the unpleasant jobs. Really? How do you make them? In the US the only mechanism for forcing people to do unpleasant jobs is the draft, and that hasn't been invoked for over 30 years. All we can do is encourage people to do unpleasant work, with money and prestige.

If there's something people still won't do, it seems as if society just has to make do without. That's what happened with domestic servants. For millennia that was the canonical example of a job "someone had to do." And yet in the mid twentieth century servants practically disappeared in rich countries, and the rich have just had to do without.

So while there may be some things someone has to do, there's a good chance anyone saying that about any particular job is mistaken. Most unpleasant jobs would either get automated or go undone if no one were willing to do them.

Two Routes

There's another sense of "not everyone can do work they love" that's all too true, however. One has to make a living, and it's hard to get paid for doing work you love. There are two routes to that destination:

The organic route: as you become more eminent, gradually to increase the parts of your job that you like at the expense of those you don't.

The two-job route: to work at things you don't like to get money to work on things you do.